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General Information
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2020 Vol.10(2): 52-56 ISSN: 2010-3697
DOI: 10.7763/IJMO.2020.V10.746

An Analysis of the Implementation of Kafka in High-Frequency Electronic Trading Environments

Vlad Bucur, Ovidiu Stan, Liviu Miclea
Abstract—Electronic trading amounts for the vast majority of all financial transactions with bonds and equities in the world. This type of trading is based largely on the brokering of messages from the buy side, brokers or financial institutions, to a sell side (usually an exchange). Since not all trading is done at the same time these messaging systems need to account for server down times, sequencing, high throughput and performance requirements. Therefore, most fintech companies employ queuing mechanism to manage the message flow. This paper analyzes the way in which Kafka, one of the premiere messaging systems currently in use, can simplify various systems in use such as message brokering, persistence or fault tolerance. The authors of this paper hope to demonstrate the use of Kafka as a messaging system, backup solution and alert broker for software operators and developers with low fault-tolerance and rigid up-time requirements.

Index Terms—Kafka, message queue, electronic trading, message broker.

Vlad Bucur, Ovidiu Stan, and Liviu Miclea are with the Department of Automation, Technical University of Cluj Napoca, Cluj, Romania (e-mail: Ovidiu.stan@aut.utcluj.ro).

[PDF]

Cite: Vlad Bucur, Ovidiu Stan, Liviu Miclea, "An Analysis of the Implementation of Kafka in High-Frequency Electronic Trading Environments," International Journal of Modeling and Optimization vol. 10, no. 2, pp. 52-56, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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